The present invention relates to a measuring apparatus for capturing the structured light, which is emitted to a target object by a pattern projector, by an image capturing device and estimating a 3D shape from the captured image by the principle of triangulation, and more particularly to a 3D shape measuring apparatus which does not have the need for previously measuring the positional relationship between the pattern projector and the image capturing device.
3D acquisition stereo systems can be categorized into two basic types: a passive stereo system and an active stereo system. The former can recover 3D shapes only from multiple images. Therefore, no special devices are necessary, and the systems are usually easy to use and convenient. However, in order to recover 3D shapes from images by passive stereo, eliminating errors for searching correspondences between images is generally difficult. Furthermore, candidates for correspondence points are usually limited to feature points on the images. Thus, interpolation is necessary to recover dense 3D points and the accuracy of the data except feature points may be unreliable.
Active stereo systems, on the other hand, utilize light projectors or laser projectors for scanning, and thus can measure 3D shapes with high precision, having no need to solve correspondence problems. In addition, dense 3D points can easily be captured in those systems by scanning lasers or by using structured light methods. Therefore, in many cases, active 3D measurement systems are adopted for scanning shapes of objects with complicated shapes.
One of the disadvantages of the active stereo systems is that these systems usually require special devices. For example, there are high precision and efficient active 3D scanners, which are equipped with servo actuators for controlling a laser projecting device. However, there is a problem in that the equipment usually becomes complex and expensive because of the necessity for accurate control of motors and so on. Also, a structured light projecting system using special light projectors are utilized, which are usually expensive.
Recently, low-cost video projectors for computers are commonly available, and it is possible to construct a practical scanning system easily based on active vision technique using those devices. Among those systems, a structured light projection method (coded structured light method) is widely used because of several advantages. For example, it can retrieve dense 3D points in a short period of time because of relatively short scanning time, and a commercially available video projector can be used, thus, there is no need for special devices such as servo motors for scanning process. Documents 1 to 5 describe examples of the researches for a structured light projection method.
Another disadvantage of active stereo systems is that calibration is required between the camera and the projector each time the conditions of the system are changed. Especially for the system based on a structured light projection method, with which a light projector and a image sensor are apart, a precalibration is required each time the system is moved, and this significantly compromises the convenience of the system. If the extrinsic calibration process can be eliminated from an active stereo system, the system can be specified and the biggest problem for active 3D scanners would be solved, thus, the system would be more practical.
Much research has been conducted based on applying self-calibration methods for passive stereo to active stereo systems by substituting a projector for one camera of the stereo paired cameras, e.g., the projector described in Document 6. However, these method are for 3D shape reconstruction in a projective space, and it is not a practical system, because many impractical assumptions are required for Euclidean reconstruction in those systems, such as an affine camera model or a plane in the scene which should be captured by the camera.
Document 1: J. Batlle, E. Mouaddib and J. Salvi “Recent progress in coded structured light as a technique to solve the correspondence problem: a survey”, Pattern Recognition, 31, 7, pp. 963-982, 1998
Document 2: D. Caspi, N. Kiryati and J. Shamir “Range imaging with adaptive color structured light”, IEEE Trans. on Patt. Anal. Machine Intell. 20, 5, pp. 470-480, 1998
Document 3: K. L. Boyer and A. C. Kak “Color-encoded structured light for rapid active ranging”, IEEE Trans. on Patt. Anal. Machine Intell., 9, 1, pp. 14-28, 1987
Document 4: S. Inokuchi, K. Sato and F. Matsuda “Range imaging system for 3-D object recognition”, ICPR, pp. 806-808, 1984
Document 5: O. Hall-Holt and S. Rusinkiewicz “Stripe boundary codes for real-time structured-light range scanning of moving objects”, In. Conf. Computer Vision, Vol. 2, pp. 359-366, 2001
Document 6: D. Fofi, J. Salvi and E. M. Mouaddib “Uncalibrated vision based on structured light”, ICRA, pp. 3548-3553, 2001